Here we demonstrate a new approach to climate model uncertainty quantification that overcomes the limitations of traditional Bayesian calibration methods in a relatively simple proof-of-concept. The approach—called calibrate-emulate-sample (CES) [1]}—consists of three successive stages, which each exploit proven concepts and methods:
